Comparing Samples from the $\mathcal{G}^0$ Distribution using a Geodesic Distance
Abstract
The distribution is widely used for monopolarized SAR image modeling because it can characterize regions with different degree of texture accurately. It is indexed by three parameters: the number of looks (which can be estimated for the whole image), a scale parameter and a texture parameter. This paper presents a new proposal for comparing samples from the distribution using a Geodesic Distance (GD) as a measure of dissimilarity between models. The objective is quantifying the difference between pairs of samples from SAR data using both local parameters (scale and texture) of the distribution. We propose three tests based on the GD which combine the tests presented in~\cite{GeodesicDistanceGI0JSTARS}, and we estimate their probability distributions using permutation methods.
Cite
@article{arxiv.1904.10499,
title = {Comparing Samples from the $\mathcal{G}^0$ Distribution using a Geodesic Distance},
author = {Alejandro C. Frery and Juliana Gambini},
journal= {arXiv preprint arXiv:1904.10499},
year = {2019}
}